Graduate Exam Abstract

kiran krishnamurthy Kinhal

M.S. Final
July 27, 2018, 2:00 pm - 3:30 pm
Engineering B-4

Abstract: The work in this thesis focuses on the design of a novel multi channel acoustical monitoring system, more specifically the development and integration of the communication system with the SCST (Sparse Coefficient State Tracking) algorithm implemented onboard. EMS is a new fully decentralized decision-making platform referred to as environmental
monitoring station (EMS) for sensor-level detection, classification, and tracking of acoustic airborne
sources in national parks. This custom-designed FPGA-based platform allows for near real-time transient source
detection and classification using the 1/3 octave spectral data extracted locally from the streaming acoustic data. Apart from source detection EMS also has the ability to monitor the surrounding environment and collect information related to air pressure, PCB temperature, ambient temperature, etc. All of this data is then packaged in the form of a report and sent to the park station with the help of onboard GSM module. Moreover, these systems can be deployed in the form of an intelligent network to obtain a finer noise map in the national park.

Adviser: Dr. Mahmood R Azimi-Sadjadi
Co-Adviser: NA
Non-ECE Member: Dr Sudipto Ghosh
Member 3: Dr Jesse Wilson
Addional Members: NA


Program of Study:
ECE 561
ECE 452
ECE 450
ECE 451
ECE 512
ECE 699
ECE 571
ECE 580B4